System and method for predicting burn-in conditions

ABSTRACT

According to one embodiment of the invention, a method for predicting burn-in conditions includes identifying a baseline IDDQ, a baseline temperature, and a baseline IDDQ current density based on a plurality of existing burn-in data for one or more existing devices, determining a theoretical IDDQ current density for a device, determining a ratio of the theoretical IDDQ current density to the baseline IDDQ current density, determining a theoretical process metric for the device at the baseline temperature based on the ratio and the baseline IDDQ, measuring a process metric for an actual device, comparing the process metric for the actual device and the theoretical process metric for the device, and determining an actual burn-in temperature for the actual device based on the comparison.

TECHNICAL FIELD OF THE INVENTION

This invention relates generally to the field of semiconductor deviceburn-in and, more specifically, to a system and method for predictingburn-in conditions or stress conditions for semiconductor devices.

BACKGROUND OF THE INVENTION

Because of continual technological advancements in semiconductormanufacturing, geometries of semiconductor devices are shrinking. Thus,transistor density continues to grow. As process geometries shrink andleakage currents increase, a dramatic increase in device current atburn-in conditions (temperature and voltage) is seen. Burn-in conditionsmay cause extremely high IDDQ currents, which may create thermal andpower issues and could potentially cause thermal runaway on strongmaterial. Thermal runaway is a phenomenon where a device draws morecurrent as it gets hotter, which results in more self-heating and mayeventually lead to junction temperatures high enough to melt the packageand possibly the test hardware.

New model burn-in ovens facilitate meeting an increased demand forcurrent, but do little to combat the resulting thermal consequences. Forexample, the Aehr Max 4 ovens only provide temperature control on theoven level. Some expensive oven options allow for individual devicetemperature monitoring and regulation of fan control to prevent thermalrunaway, except these ovens are expensive and do not facilitate optimalburn-in conditions. Consequently, common temperature set points must befound that will accommodate a wide range of potential device currentneeds.

SUMMARY OF THE INVENTION

According to one embodiment of the invention, a method for predictingburn-in conditions includes identifying a baseline IDDQ, a baselinetemperature, and a baseline IDDQ current density based on a plurality ofexisting burn-in data for one or more existing devices, determining atheoretical IDDQ current density for a device, determining a ratio ofthe theoretical IDDQ current density to the baseline IDDQ currentdensity, determining a theoretical process metric for the device at thebaseline temperature based on the ratio and the baseline IDDQ, measuringa process metric for an actual device, comparing the process metric forthe actual device and the theoretical process metric for the device, anddetermining an actual burn-in temperature for the actual device based onthe comparison.

Some embodiments of the invention provide numerous technical advantages.Other embodiments may realize some, none, or all of these advantages.For example, in one embodiment, correct burn-in conditions for a newdevice may be ascertained without having to rely on experimental data.This may be especially important for application specific integratedcircuits, in which the volume of devices manufactured is relativelysmall. Because process geometries are continually shrinking, havingcorrect burn-in conditions potentially increases yield by eliminatingthe possibility of thermal runaway on strong material.

Other technical advantages are readily apparent to one skilled in theart from the following figures, descriptions, and claims.

BRIEF DESCRIPTION OF THE DRAWINGS

For a more complete understanding of the invention, and for furtherfeatures and advantages, reference is now made to the followingdescription, taken in conjunction with the accompanying drawings, inwhich:

FIG. 1 is a graph illustrating the relationship between process metricand IDDQ at different burn-in temperatures for devices according to oneembodiment of the present invention; and

FIG. 2 is a flowchart illustrating a method for predicting burn-inconditions according to one embodiment of the present invention.

DETAILED DESCRIPTION OF EXAMPLE EMBODIMENTS OF THE INVENTION

Example embodiments of the present invention and their advantages arebest understood by referring now to FIGS. 1 and 2 of the drawings, inwhich like numerals refer to like parts.

FIG. 1 is a graph 100 illustrating the relationship between a processmetric 102 and a quiescent current draw (“IDDQ”) 104 at differentburn-in temperatures 106 for semiconductor devices according to oneembodiment of the present invention. The particular process metricillustrated in FIG. 1 is N2P. However, this process metric is used forexample purposes only. The present invention contemplates any suitableprocess metric. As is well known in the semiconductor industry, theprocess metric may change from chip-to-chip depending on the design ofthe chip. IDDQ 104 is expressed in FIG. 1 as mA, but may be expressed inother suitable units. The IDDQ of a particular chip is the amount ofcurrent running through the chip in a quiescent state when there is noinput signal applied thereto. Burn-in temperature 106 is illustrated inFIG. 1 as being expressed in degrees Celsius, but may be expressed inother suitable temperature units.

As illustrated in FIG. 1, IDDQ 104 rises exponentially with processmetric 102. This exponential relationship becomes greater as burn-intemperature 106 increases. Because of continual technologicaladvancements in semiconductor device manufacturing, geometries ofsemiconductor devices are shrinking. As process geometries shrink,leakage currents increase. Thus, a dramatic increase in device currentat burn-in conditions is seen. Burn-in conditions may cause extremelyhigh IDDQ currents, which may create thermal and power issues and couldpotentially cause thermal runaway. Thermal runaway is a phenomenon wherea semiconductor device draws more current as it gets hotter, whichresults in more self-heating and may eventually lead to junctiontemperatures high enough to melt the package and possibly the testhardware. Thus, as illustrated by FIG. 1, a max IDDQ, as indicated byreference numeral 108, generally represents the maximum IDDQ that aparticular semiconductor device can experience before potentially goinginto thermal runaway. Therefore, as process metric 102 of a particulardevice increases, the burn-in temperature 106 for that particular deviceneeds to decrease to avoid thermal runaway or problem.

Therefore, according to the teachings of one embodiment of the presentinvention, a method is disclosed for predicting the correct burn-intemperature for a particular device for which there is no experimentalburn-in data. An example embodiment of such a method is illustrated anddescribed below in conjunction with the flowchart of FIG. 2. Althoughthis detailed description discusses burn-in of semiconductor devices,any suitable stressing of semiconductor devices is contemplated by thepresent invention. Correctly ascertaining the burn-in temperature for anew semiconductor device without having to rely on experimental data maybe advantageous, especially for relatively low volume parts such asapplication-specific integrated circuits (“ASICs”). Having the correctburn-in temperature for new semiconductor devices in which the processgeometries are smaller than previous geometries potentially increasesyield by eliminating the possibility of thermal runaway, especially inhigh leakage material.

FIG. 2 is a flowchart illustrating an example method for predictingburn-in conditions according to one embodiment of the invention. Theexample method begins at step 200 in which a plurality of baselineconditions are identified. In this illustrated embodiment, the baselineconditions identified are a baseline IDDQ, a baseline temperature, and abaseline IDDQ current density. Other suitable baseline conditions arecontemplated by the present invention, such as a baseline processmetric, a baseline voltage, and a baseline change in temperature perchange in process metric. These baseline conditions are identified baseon a plurality of existing burn-in data for one or more existingsemiconductor devices. The greater number of devices, the betteraccuracy that may be obtained for the baseline conditions. Any suitablestatistical analysis, such as a regression analysis, may be utilized todetermine the baseline conditions.

For example, according to one embodiment of the invention, a pluralityof process metrics, a plurality of burn-in temperatures, and a pluralityof burn-in voltages for respective semiconductor devices are plotted ona graph. Then a regression analysis (or other statistical analysis) isutilized to express the baseline IDDQ as a function of a baselineprocess metric, a baseline burn-in temperature, and a baseline burn-involtage. In a particular embodiment of the invention, the baseline IDDQmay be expressed as follows: baseline IDDQ=10^([w+x(V)+y(T)+z(N2P)]),where V=the baseline voltage; T=the baseline temperature; and N2P=thebaseline process metric. The present invention contemplates the baselineIDDQ being expressed in other forms depending on the type of burn-indata utilized for the baseline conditions.

Based on existing ASICs, burn-in data for these devices were utilized toobtain the following specific baseline conditions. A baseline processmetric of 1350, a baseline burn-in temperature of 105° C., a baselineIDDQ of 300 mA, a baseline IDDQ current density of 0.11, and a baselinechange in temperature per change in process metric of 10° C. per onehundred process metric. Again, other suitable baseline conditions may beutilized within the teachings of the present invention. For example,depending on the type of risk that is willing to be taken, the change inburn-in temperature per change in process metric may be anywhere from10–15° C. The baseline voltage utilized in this example embodiment is1.7 volts; however, other suitable baseline voltages may also beutilized.

After the baseline conditions are identified, a burn-in temperature fora new semiconductor device or a semiconductor device that has not beenburned-in before may be determined by the following steps. At step 202,a theoretical IDDQ current density for a particular device isdetermined. This may be based on design information for that device andmay be estimated using any suitable estimation tools. A ratio of thetheoretical IDDQ current density to the baseline IDDQ current density isdetermined at step 204. Based on this ratio and the IDDQ equationidentified above in the baseline conditions, a theoretical processmetric for the device at the baseline temperature is determined, asindicated by step 206. Referring to the equation as indicated above asan example, the baseline voltage, baseline temperature, and baselineIDDQ are known and because of the ratio it is known whether or not toreduce or increase the baseline IDDQ based on the ratio of thetheoretical and baseline current densities, as determined at step 204.The only unknown is the theoretical process metric. The equation maythen be solved to determine the theoretical process metric for thedevice. Thus, the process metric and burn-in temperature for theparticular device is theoretically known.

Finally, to determine the correct burn-in temperature for an actualdevice, a process metric for an actual device is measured at step 208.This measuring may be done with varying levels of granularity. Forexample, the measuring may include averaging a plurality of processmetrics for respective actual devices formed on a single wafer or aplurality of wafers of a particular lot. Other suitable measurements mayalso be utilized, such as measuring specific zones of a wafer, or takingthe maximum process metric of a particular wafer or wafer lot.

A difference between the process metric of the actual device and thetheoretical process metric for the device that was determined in step206 is determined at step 212. The baseline temperature is adjusted toan actual burn-in temperature if the difference exceeds a predetermineddifference, as indicated by step 214. Thus, the correct burn-intemperature may be identified for the actual device based on thetheoretical process metric and baseline burn-in temperature. Forexample, as indicated above, a change in burn-in temperature per changein process metric may be found to be approximately 10° C. per a changeof one hundred process metric. If the process metric for the actualdevice was found to be 1250 and the theoretical process metric for thedevice was determined to be 1350, then the burn-in temperature may beincreased by 10° C. from 105° C. to 115° C. Conversely, if the processmetric for the actual device was one hundred more than the theoreticalprocess metric, then the burn-in temperature may be reduced by 10° C. to95° C. The actual burn-in temperatures for particular devices may thenbe stored in a database, as indicated by 216, so that burn-in personnelcan easily retrieve the burn-in temperature for a particular device,wafer, or lot of wafers with the assurance that problems such as thermalrunaway will not occur during burn-in.

Although embodiments of the invention and their advantages are describedin detail, a person skilled in the art could make various alterations,additions, and omissions without departing from the spirit and scope ofthe present invention, as defined by the appended claims.

1. A method for predicting burn-in conditions, comprising: identifying abaseline IDDQ, a baseline temperature, and a baseline IDDQ currentdensity based on a plurality of existing burn-in data for one or moreexisting devices; determining a theoretical IDDQ current density for adevice; determining a ratio of the theoretical IDDQ current density tothe baseline IDDQ current density; determining a theoretical processmetric for the device at the baseline temperature based on the ratio andthe baseline IDDQ; measuring a process metric for an actual device;comparing the process metric for the actual device and the theoreticalprocess metric for the device; and determining an actual burn-intemperature for the actual device based on the comparison.
 2. The methodof claim 1, further comprising storing the actual burn-in temperature ina database.
 3. The method of claim 1, wherein identifying the baselineIDDQ based on the plurality of existing burn-in data for one or moreexisting devices comprises: plotting a process metric for each device;plotting a burn-in temperature for each device; plotting a burn-involtage for each device; and utilizing regression analysis to expressthe baseline IDDQ as a function of a baseline process metric, a baselineburn-in temperature, and a baseline burn-in voltage.
 4. The method ofclaim 3, wherein the baseline IDDQ is expressed as baselineIDDQ=10^([w+x(V)+y(T)+z(N2P)]) where V=a baseline voltage; T=thebaseline temperature; and N2P=a baseline process metric.
 5. The methodof claim 1, wherein measuring the process metric for the actual devicecomprises averaging a plurality of process metrics for respective actualdevices formed on a single wafer.
 6. The method of claim 1, whereinmeasuring the process metric for the actual device comprises averaging aplurality of process metrics for respective actual devices formed on aplurality of wafers of a lot.
 7. The method of claim 1, whereindetermining the actual burn-in temperature for the actual device basedon the comparison comprises: determining a difference between theprocess metric for the actual device and the theoretical process metricfor the device; and adjusting the baseline temperature if the differenceexceeds a predetermined difference.
 8. The method of claim 7, whereinthe predetermined difference is a process metric of one hundred.
 9. Themethod of claim 7, wherein adjusting the baseline temperature comprisesadjusting the baseline temperature between ten and fifteen degreesCelsius.
 10. A method for predicting burn-in conditions, comprising:identifying a plurality of baseline conditions based on a plurality ofexisting burn-in data for one or more existing devices, comprising:determining a baseline process metric; determining a baseline burn-intemperature; determining a baseline burn-in voltage; determining abaseline IDDQ expressed as a function of the baseline process metric,the baseline burn-in temperature, and the baseline burn-in voltage; anddetermining a baseline IDDQ current density; determining a theoreticalIDDQ, a theoretical area, and a theoretical IDDQ current density for adevice; determining a ratio of the theoretical IDDQ current density tothe baseline IDDQ current density; determining a theoretical processmetric for the device at the baseline temperature based on the ratio andthe baseline IDDQ; measuring a process metric for an actual device;determining a difference between the process metric for the actualdevice and the theoretical process metric for the device; and adjustingthe baseline temperature if the difference exceeds a predetermineddifference.
 11. The method of claim 10, further comprising storing theactual burn-in temperature in a database.
 12. The method of claim 10,wherein identifying the baseline IDDQ based on the plurality of existingburn-in data for one or more existing devices comprises: plotting aprocess metric for each device; plotting a burn-in temperature for eachdevice; plotting a burn-in voltage for each device; and utilizingregression analysis to express the baseline IDDQ as a function of abaseline process metric, a baseline burn-in temperature, and a baselineburn-in voltage.
 13. The method of claim 11, wherein the baseline IDDQis expressed as baseline IDDQ=10^([w+x(V)+y(T)+z(N2P)]) where V=abaseline voltage; T=the baseline temperature; and N2P=a baseline processmetric.
 14. The method of claim 10, wherein measuring the process metricfor the actual device comprises averaging a plurality of process metricsfor respective actual devices formed on a single wafer.
 15. The methodof claim 10, wherein measuring the process metric for the actual devicecomprises averaging a plurality of process metrics for respective actualdevices formed on a plurality of wafers of a lot.
 16. The method ofclaim 10, wherein the predetermined difference is a process metric ofone hundred.
 17. The method of claim 10, wherein adjusting the baselinetemperature comprises adjusting the baseline temperature between ten andfifteen degrees Celsius.
 18. A method for predicting burn-in conditions,comprising: receiving existing burn-in data for a plurality of existingdevices; plotting respective process metrics for the exiting devices;plotting respective burn-in temperatures for the existing devices;plotting respective burn-in voltages for the existing devices; utilizingstatistical analysis to express a baseline IDDQ as a function of abaseline process metric, a baseline burn-in temperature, and a baselineburn-in voltage based on the respective process metrics, the respectiveburn-in temperatures, and the respective burn-in voltages; identifying abaseline IDDQ current density from the existing burn-in data;determining a theoretical IDDQ current density for a device; determininga ratio of the theoretical IDDQ current density to the baseline IDDQcurrent density; determining a theoretical process metric for the deviceat the baseline temperature based on the ratio and the baseline IDDQ;measuring a process metric for an actual device; determining adifference between the process metric for the actual device and thetheoretical process metric for the device; and adjusting the baselinetemperature between ten and fifteen degrees Celsius if the differenceexceeds approximately one hundred.
 19. The method of claim 18, whereinthe baseline process metric is between 1250 and 1450 and the baselineburn-in temperature is between 95° C. and 115° C.
 20. The method ofclaim 18, wherein the baseline IDDQ current density is between 0.05 and0.15.